System and method for efficient non-overlapping partitioning of rectangular regions of interest in multi-channel detection

ABSTRACT

A system and method in a multi-channel detection system for multi-rate filter bank applications for converting overlapping rectangular two-dimensional (2D) regions into a new set of non-overlapping rectangular regions for the efficient reconstruction of a signal wherein each non-overlapping region has a maximum extent in a major dimension is described. Overlapping regions are split into marked regions in a non-uniform grid and merged along the major dimension and along the minor dimension to form non-overlapping regions wherein no two non-overlapping rectangular regions have an adjacent edge orthogonal to the major dimension thereby increasing the efficiency of data compression and reducing error-rates.

BACKGROUND

In multi-rate filter bank applications (e.g. a wideband channelizer)where overlapping and non-overlapping 2D rectangular regions representdifferent frequency bands of interest at different times and overdifferent time durations, different layers of frequency resolution canpotentially generate overlaps causing multiple detection within onetime-frequency cell. These time frequency overlaps result in lessefficient compression due to multiple transmissions of the same data.Additionally since signal reconstruction errors increase for smallertime-frequency regions, the most accurate reconstruction corresponds toregions with the largest bandwidth and longest time-duration. FIG. 1shows twenty exemplary 2D rectangular regions of interest showing theoverlaps between different regions.

In binary image coding where the compressed data corresponding to justthe locations and sizes of the non-zero “black” regions is sufficientfor reconstructing the image, an iterative approach is used. Knownmethods of binary image coding consists of three main steps: (a) araster-scan through the columns and then the rows of the image to findthe next non-zero pixel corresponding to a top-left corner, (b) acolumn-wise scan to find the top-right corner at the first zero pixeland (c) a row-wise scan to find either the bottom-left or bottom-rightcorner corresponding to a zero pixel between the left and right sides orto a non-zero pixel in the columns directly outside the left and rightsides. However, this method does not provide the set of non-overlappingregions with either maximum vertical-extent or maximumhorizontal-extent. Also, the method cannot be directly applied to a setof overlapping rectangular regions to determine the optimal set ofnon-overlapping regions.

A known prior art compression technique for binary text images uses asimilar approach. The prior art technique partitions the non-zeroregions into non-overlapping and fully overlapping regions, defines thevertices and assigns specific codes to the converted rectangularregions' vertices reflective of their status as non-overlapping or fullyoverlapping regions. This method does not provide a set ofnon-overlapping rectangular regions encompassing the entire marked area,nor does it allow for a maximum extent in one dimension.

For data compression, error reduction, and other reasons, it isdesirable to employ a method for converting overlapping rectangulartwo-dimensional (2D) regions into a new set of non-overlappingrectangular regions to thereby allow for efficient reconstruction of asignal output from the filter bank. It is further desirable that theabove method determine the smallest set of non-overlapping rectangularregions with the maximum extent in either the vertical or the horizontaldimension since signal reconstruction errors are larger for smallertime-frequency regions. The most accurate reconstruction corresponds toregions with the largest bandwidth and longest time duration, i.e.larger time frequency regions.

Accordingly, it is an object of the disclosed subject matter to obviatemany of the above problems in the prior art and to provide a novelmethod in a multi-channel detection system for transforming a pluralityof overlapping two-dimensional rectangular regions into non-overlapping2D rectangular regions wherein each non-overlapping region has a maximumextent in a major dimension (i.e. either horizontally or vertically). Anembodiment of the method includes the steps of: splitting theoverlapping regions into marked regions in a non-uniform grid; mergingthe marked grid regions along the major dimension and along the minordimension to thereby form non-overlapping regions wherein no twonon-overlapping rectangular regions have an adjacent edge orthogonal tothe major dimension.

It is another object of the disclosed subject matter to provide a novelimprovement of a method for compressing data. One embodiment of themethod comprises the step of transforming overlapping two-dimensionalrectangular regions into non-overlapping 2D rectangular regions whereinthe non-overlapping rectangular regions have a maximum extent in onedimension.

It is yet another object of the disclosed subject matter to provide, ina time-frequency window of interest, a novel method of excising theoverlapping portion of two-dimensional rectangular areas. An embodimentof the method comprises the steps of forming a non-uniformtwo-dimensional grid using the coordinates of the overlappingrectangular areas; splitting the overlapping 2D rectangular areas intonon-uniform grid units, and combining adjacent tagged grid units intonon-overlapping rectangular regions defined by major edges and minorcorners.

It is still another object of the disclosed subject matter to provide anovel method of reconstructing a coverage area defined by overlappingtwo-dimensional rectangular regions with non-overlapping 2D rectangularregions. An embodiment of the method comprises the steps of forming anon-uniform two-dimensional grid using the coordinates of theoverlapping rectangular areas; splitting the overlapping 2D rectangularareas into non-uniform grid units; and combining adjacent tagged gridunits into non-overlapping rectangular regions defined by major edgesand minor corners.

It is an additional object of the disclosed subject matter to provide anovel improvement for a method in a Cartesian space defined by afrequency domain and a time domain for transforming a plurality ofoverlapping rectangular regions into a plurality of non-overlappingrectangular regions. An embodiment of the method comprises theimprovement wherein none of the non-overlapping rectangular regionsshare a common edge orthogonal to a preferred dimension.

It is still an additional object of the disclosed subject matter toprovide, in a time-frequency window of interest, a novel method ofexcising the overlapping portion of overlapping two-dimensionalrectangular areas comprising the step of transforming the overlappingrectangular areas into non-overlapping rectangular areas by theimprovement wherein none of the non-overlapping rectangular areas sharea common edge orthogonal to a preferred dimension.

These and many other objects and advantages of the disclosed subjectmatter will be readily apparent to one skilled in the art to which thedisclosure pertains from a perusal or the claims, the appended drawings,and the following detailed description of the preferred embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a representation of overlapping rectangular regions in anon-uniform grid

FIG. 2 is a representation of the coverage indicator matrix for theoverlapping rectangular regions in FIG. 1.

FIG. 3 is a representation of the non-overlapping rectangular regionscreated from the overlapping rectangular regions in FIG. 1 according toan embodiment of the disclosed subject matter.

FIG. 4 is a representation of non-overlapping rectangular regionscreated from the overlapping rectangular regions in FIG. 1 according toknown prior art.

FIG. 5 is a graph relating number of non-overlapping rectangular regionsobtained via the disclosed subject matter and known prior art.

FIG. 6 is a graph relating the number of adjacent edges in a preferreddimension for an embodiment of the disclosed subject matter and a knownprior art method.

DETAILED DESCRIPTION

A method according to an embodiment of the disclosed subject mattercomprises three steps: (1) determining a non-uniform 2D gridcorresponding the all the overlapping rectangular region boundaries, (2)determining the non-uniform grid rectangles covered by one or more ofthe overlapping rectangles and (3) combining directly adjacent coveredgrid regions to find the smallest set of non-overlapping rectangles withthe maximum extent either vertically or horizontally.

For the i^(th) 2D rectangular region R_(i) 10 in a set of N possiblyoverlapping rectangular regions 1 as shown in FIG. 1, let x_(0,i),x_(1,i), y_(0,i), y_(1,i) denote the minimum (left) x-value 11, maximum(right) x-value 12, minimum (bottom) y-value 13 and maximum (top)y-value 14, respectively. The four vectors x₀=[x_(0,1), x_(0,2), . . . ,x_(0,N)]^(T), x₁=[x_(1,1), x_(1,2), . . . , x_(1,N)]^(T), y₀=[y_(0,1),y_(0,2), . . . , y_(0,N)]^(T) and y₁=[y_(1,1), y_(1,2), . . . ,y_(1,N)]^(T) represent the 4N corner locations of all N rectangles(where [ ]^(T) is the transpose vector). It is desirable to find the setof non-overlapping rectangular regions covering the same areas as theoverlapping regions and with the maximum extent in the “major”dimension. Without loss of generality, the vertical dimension is assumedto be the “major” dimension in the current discussion, wherein thevertical dimension or horizontal dimension may correspond to parameterssuch as time or frequency. The other dimension is then defined as theminor dimension. For the case where the “major” dimension is horizontal,x₀ is interchanged with y₀ and x₁ with y₁.

Determining a Non-Uniform Grid

An initial step in an embodiment of the disclosure is to define anon-uniform grid corresponding to the unique x-values and uniquey-values of a set of possibly overlapping rectangular regions. Let theN_(x)×1 vector x_(g) denote the unique x values in the 2N×1 vector [x₀^(T), x₁ ^(T)]^(T), sorted in ascending order, i.e.min(x₀)=x_(g,1)<x_(g,2)< . . . <x_(g,N) _(x) =max(x₁). Similarly, letthe N_(y)×1 vector y_(g) denote the sorted unique y values in the vector[y₀ ^(T), y₁ ^(T)]^(T), i.e. min(y₀)=y_(g,1)<y_(g,2)< . . . <y_(g,N)_(y) =max(y₁). FIG. 1 shows an example of a set of 20 randomly generatedoverlapping rectangular regions (i.e. N=20), some of which overlapothers, and the resulting non-uniform 2D grid derived from the unique xand y values of the rectangular regions. The non-uniform grid is shownby the dashed-lines 5 and tick-marks along each axis. The solid linesindicate the edges of the different rectangular regions. By thedefinitions of x_(g) and y_(g), the number of grid points is(N_(x)N_(y))≦(2N)². In FIG. 1, N_(x)=N_(y)=29 and 2N=40.

Determining the Non-Uniform Grid Regions Covered by Rectangles

A latter step in the process is to determine which single row/singlecolumn non-uniform grid regions are covered by one or more of therectangular regions represented by x₀, x₁, y₀, and y₁. Let theN_(y)×N_(x) matrix C be a coverage indicator matrix where C_(i,j)=1 ifx_(0,n)≦x_(g,j)<x_(1,n) and y_(0,n)≦y_(g,i)<y_(1,n) for any n=1, . . . ,N and otherwise C_(i,j)=0. The small dot symbols 22 in FIG. 2 indicatethe non-zero elements in C 20 for the rectangular regions shown in FIG.1, note that the x and y axes of FIG. 2 have been transformed torepresent the cardinality of the unique x and y values, respectively.The last row and last column of C consist of all zeros (shown as blanks)in FIG. 2, since x_(0,n)<x_(1,n)≦x_(g,N) _(x) andy_(0,n)<y_(1,n)≦y_(g,N) _(y) for any n=1, . . . , N. At this point, aset of non-overlapping single column or single row rectangles can befound directly from the row and column indices of the non-zero elementsof matrix C 20. However, this set of covered grid rectangle regionscorresponds to the largest partitioning of the covered regions. A muchmore efficient partitioning results from grouping multiple covered gridregions that are directly adjacent to each other.

Combining Directly Adjacent Covered Grid Regions

To determine a smaller set of non-overlapping rectangles, adjacentcovered grid regions are grouped or merged, first in the major(vertical) dimension and second in the minor (horizontal) dimension.Again the major and minor dimensions are assigned for illustration onlyand are not intended to be limiting the embodiment of the disclosedsubject matter in anyway. Grouping adjacent covered grid regions can beequivalently expressed in terms of edge-detection for the “binary image”formed by the coverage matrix C 20. The top and bottom “edges” in C 20correspond to the non-zero 1^(st)-order differences in the rows of C 20.Since any “ones” (small dots 22) in the 1^(st) row of C 20 correspond tobottom edges of tall-narrow single column rectangles, let the1^(st)-order row-difference matrix be defined as

$\left\lbrack C_{\Delta\; y} \right\rbrack_{i,j} = \left\{ \begin{matrix}{C_{i,j},} & {i = 1} \\{{C_{i,j} - C_{{i - 1},j}},} & {i > 1}\end{matrix} \right.$

The rows of the non-zero elements of C_(Δy) 30 correspond to eitherbottom edges 31, where [C_(Δy)]_(i,j)=1, or top edges 32, where[C_(Δy)]_(i,j)=−1, as shown in FIG. 2. The set ofmultiple-row/single-column non-overlapping rectangles can be representedby the row and columns indices of the non-zero elements of C_(Δy) 30.Let the N_(C)×1 vectors e_(y) ₀ and e_(y) ₁ denote the row indicescorresponding to positive 1 and negative 1 elements in C_(Δy) 30, i.e.the bottom edges and top edges, respectively. Let the N_(C)×1 vectore_(x) ₀ likewise denote the column indices corresponding to the positive“1” elements in C_(Δy) 30. It is assumed that the index vector e_(x) ₀is formed via a “raster-scan” down the 1^(st) column of C_(Δy) 30, thenthe 2^(nd) column, and so on.

The next step is to group any multiple-row/single-column rectangles inadjacent columns that have identical row indices. This can be performedvia a corner-detection process similar to the previous edge-detectionstep. Since the corners of the multiple-row/multiple-column rectanglesare desired, 1^(st)-order differences are computed across the columns ofC_(Δy) rather than C itself. Let the N_(y)×N_(x) matrix C_(ΔxΔy) 40denote the column-wise 1^(st)-order differences of C_(Δy) 30, i.e.

$\left\lbrack C_{\Delta\; x\;\Delta\; y} \right\rbrack_{i,j} = \left\{ \begin{matrix}{\left\lbrack C_{\Delta\; y} \right\rbrack_{i,j},} & {j = 1} \\{{\left\lbrack C_{\Delta\; y} \right\rbrack_{i,j} - \left\lbrack C_{\Delta\; y} \right\rbrack_{i,{j - 1}}},} & {j > 1}\end{matrix} \right.$

The bottom-left and top-right corners correspond to where C_(ΔxΔy)=1while the top-left and bottom-right corners correspond to whereC_(ΔxΔy)=−1. The locations of the corners, as well as the top and bottomedges, are shown in FIG. 2. The squares, triangles and circlescorrespond to non-zero elements of C 20, C_(Δy) 30, and C_(ΔxΔy) 40,respectively. The top and bottom edges are further indicated by theorientation of the triangle symbols. The bottom edges coincide withnon-zero elements of C 20, while the top-edges do not.

Given the matrix C_(ΔxΔy) 40 and index vectors e_(y) ₀ , e_(y) ₁ , ande_(x) ₀ , the multiple-row/multiple-column non-overlapping rectanglescan be determined according to an embodiment of the disclosed subjectmatter via the following procedure.

Let n=1 and let N_(y)×N_(x) matrix D=0.

For i=1, . . . , N_(C), let i_(y)=[e_(y) ₀ ]_(i) and I_(x)=[e_(x) ₀]_(i)

If D_(i) _(y) _(,i) _(x) =0, then

Assign [{tilde under (e)}_(y) ₀ ]_(n)=[e_(y) ₀ ]_(i), [{tilde under(e)}_(y) ₁ ]_(n)=[e_(y) ₁ ]_(i), and [{tilde under (e)}_(x) ₀]_(n)=[e_(x) ₀ ]_(i), and let m_(y)=[e_(y) ₁ ]_(i).

${{Let}\mspace{14mu} b_{j}} = \left\{ {\begin{matrix}{0,} & {j \leq i_{x}} \\{{\sum\limits_{m = i_{y}}^{m_{y}}{\left\lbrack C_{\Delta\; x\;\Delta\; y} \right\rbrack_{m,j}}},} & {j > i_{x}}\end{matrix}.} \right.$

Let m_(x) denote the index of the first non-zero element of vector b.

Assign [{tilde under (e)}_(x) ₁ ]_(n)=m_(x) and D_(r,c)=1 fori_(y)≦r≦m_(y) and i_(x)≦c≦m_(x).

Increment n=n+1

Each element of matrix D indicates if the grid-region corresponding tothat row and column has already been assigned to amultiple-row-/multiple-column rectangle. The N_(x)×1 vector b indicatesif matrix C_(ΔxΔy) 40 has any non-zero elements from row i_(y) to rowm_(y) in the columns greater than i_(x). It is used to find theright-edge of the multiple-row/multiple-column rectangle withbottom-left at (i_(x), i_(y)) and top-left at (i_(x), m_(y)). Thevectors, {tilde under (e)}_(x) ₀ , {tilde under (e)}_(y) ₀ , {tildeunder (e)}_(x) ₁ and {tilde under (e)}_(y) ₁ consist of the indicescorresponding to the bottom-left and top-right corners of themultiple-row/multiple-column non-overlapping rectangles. Thenon-overlapping rectangles on the non-uniform grid correspond to thevectors {tilde under (x)}₀, {tilde under (x)}₁, {tilde under (y)}₀ and{tilde under (y)}₁ with elements given by [{tilde under(x)}₀]_(i)=x_(g)([{tilde under (e)}_(x) ₀ ]_(i)), [{tilde under (x)}₁],=x_(g)([{tilde under (e)}_(x) ₁ ]_(i)), [{tilde under(y)}₀]_(i)=y_(g)([{tilde under (e)}_(y) ₀ ]_(i)) and [{tilde under(y)}×₁]_(i)=y_(g)([{tilde under (e)}_(y) ₁ ]_(i)), respectively.

For comparison, non-overlapping regions determined based on the priorart approach are shown in FIG. 4. The prior art and the disclosedmethods differ in how the non-overlapping regions are determined fromthe coverage indicator matrix C.

For the example of rectangles regions shown in FIG. 1, the resultingnon-overlapping rectangles, computed via the steps above for anembodiment of the disclosed subject matter, are shown in FIG. 3. All thenon-overlapping rectangles in FIG. 3 extend over multiple vertical gridregions and several extend over multiple horizontal grid regions.

The rectangles in FIG. 3 may be directly adjacent to each other in theminor dimension, i.e. horizontally (with a right-edge against aleft-edge), but not in the major dimension, i.e. vertically (with atop-edge against a bottom-edge). In other words, between any tworectangles there are no adjacent edges orthogonal to the majordimension. This feature is desirable in signal reconstruction frommulti-rate filter banks where the errors in the reconstructed signaltend to increase with channelization into narrower bandwidth channels.Similarly with reconstruction filter banks, the reconstruction improvesfor longer time durations so the desired rectangular regions should havethe maximum time-extent for each sub-channel.

The non-overlapping regions determined from matrix C using the prior artmethod are shown in FIG. 4. While the number of non-overlappingrectangles is smaller with the prior art approach, 23 versus 25 for theabove described embodiment of the inventive method, the vertical extent(major dimension) is not maximized for a fixed value of x using theprior art approach. This can be seen from the occurrence of regions 45,as shown in FIG. 4, that are adjacent to other regions directly above orbelow, i.e. with top-edges against bottom edges.

An embodiment of the disclosed subject matter generally gives a largernumber of rectangles due to the constraint on the extent of therectangles in the major dimension. This can be seen from the twohistograms shown in FIG. 5, where the mode of the embodiment of thedisclosed subject matter's histogram is generally to the right of themode of the prior art histogram. However, the number of non-overlappingregions resulting from using the above described inventive embodiment ofthe disclosed subject matter is typically only slightly larger than thenumber of non-overlapping regions resulting from using the prior art.

The performance of the two methods with respect to maximizing the extentof the non-overlapping regions in the major dimension can be measuredfrom the number of undesirable shared edges between any two regions.When the major dimension is vertical, this corresponds to the number oftimes a non-overlapping region is directly above or below anotherregion, i.e. bottom-edge against top-edge. In FIG. 6, the histograms ofthe number of undesirable shared edges are shown for the prior art andan inventive embodiment of the disclosed subject matter. Two histogramsare shown for the prior art, corresponding to row-then-column andcolumn-then-row raster-scans. Based on 1000 Monte Carlo trials, themethod according to an embodiment of the disclosed subject matter had noundesirable edges, adjacent edges orthogonal to the major dimension. Incontrast, the prior art results in adjacent non-overlapping regions inthe major dimension regardless of the order of the raster-scan.

In an embodiment of the disclosed subject matter, rectangular regionsdefining bandwidth, time slots or other particular sets of values, maylikewise by implemented. Hard indices can be established for rectangularregions which restrict merging with adjacent covered regions in thedimension of interest. An embodiment can also use erosion and/ordilation morphological operations on the coverage indicator matrix, or“image”, to avoid situations with many closely spaced but not directlyadjacent time-frequency regions corresponding to greater computationthan that for a few larger time-frequency regions over the same areas.

In another embodiment of the disclosed subject matter, the abovedescribed procedure may be implemented in machine readable softwarecode, in firmware, or in hardware including, but not limited tointegrated circuits (IC), application specific integrated circuits(ASICs), printed wiring boards (PWB), discrete logic circuits, etc.

While preferred embodiments of the present invention have beendescribed, it is to be understood that the embodiments described areillustrative only and that the scope of the invention is to be definedsolely by the appended claims when accorded a full range of equivalence,many variations and modifications naturally occurring to those of skillin the art from a perusal thereof.

1. In a multi-channel detection system, a method of transforming aplurality of overlapping two-dimensional rectangular regions positionedin a plane with two orthogonal axes into non-overlapping two-dimensionalrectangular regions wherein each non-overlapping region has a maximumextent in a major dimension oriented parallel to one of the orthogonalaxes comprising the steps of: an electronic device performing the stepsof: (a) splitting the overlapping regions into marked regions in anon-uniform grid; (b) merging the marked regions along the majordimension and along the minor dimension to form non-overlappingrectangular regions, wherein no two non-overlapping rectangular regionshave an adjacent edge orthogonal to the major dimension.
 2. The methodof claim 1 wherein the step of creating the marked regions comprises thesteps of: (a) obtaining for each of the overlapping rectangular regions,corner coordinates comprising a major dimension component and a minordimension component; (b) transforming the coordinates into respectivenon-uniform grid indices by assigning each major dimension componentvalue a corresponding major dimension component value in the non-uniformgrid and assigning each minor dimension component value a correspondingminor dimension component value in the non-uniform grid; (c) markingrectangular area defined by the corresponding non-uniform grid indicesfor each of the plurality of overlapping rectangular regions.
 3. Themethod of claim 1 wherein the step of merging the marked regions alongthe major dimension comprises the steps of: (a) establishing sequentialminor non-uniform grid indices along the axis orthogonal to the majordimension corresponding cardinally to the unique minor axis coordinatesof the overlapping rectangular regions and establishing sequential majornon-uniform grid indices along the major dimension correspondingcardinally to the unique major axis coordinates of the overlappingrectangular regions; (b) joining adjacent marked regions sharing thesame minor axis non-uniform grid indices along the major axis to createsets of marked regions along the major dimension, each set bound in themajor dimension by the greatest and least major non-uniform grid indicesof the marked regions within the respective set; (c) joining sets ofmarked regions with the same major dimension bounds along the minordimension to create non-overlapping rectangular regions; (d) obtainingthe corner coordinates for each of the non-overlapping rectangularregions.
 4. The method of claim 2, wherein the corresponding majordimension non-uniform grid indices are sequential integers and thecorresponding minor dimension non-uniform grid indices are sequentialintegers.
 5. The method of claim 1, wherein the major dimension isvertical and the minor is horizontal.
 6. The method of claim 1, whereinone of the orthogonal axis represents time and the other orthogonal axisrepresents frequency.
 7. A method of compressing data comprising thestep of transforming a set of overlapping two dimensional rectangularregions positioned in a plane defined by two orthogonal axes into a setof non-overlapping two dimensional rectangular regions, the improvementcomprising an electronic device performing the steps of: splitting theset of overlapping two dimensional rectangular regions into regions in anon-uniform grid and merging the regions along each of the twoorthogonal axes to form non-overlapping rectangular regions, wherein thenon-overlapping rectangular regions comprise a maximum extent in onedimension parallel to one of the orthogonal axes.
 8. A method ofreconstructing a coverage area of a set of two dimensional overlappingrectangular regions on a plane with two orthogonal axes defining a majordimension and a minor dimension with a set of non-overlappingrectangular regions comprising the steps of: an electronic deviceperforming the steps of: defining non-uniform grid on the orthogonalaxes; defining the coverage area on the non-uniform grid; creatingsingle column/single row rectangles matching the coverage area on thenon-uniform grid; assigning coordinates to the corners of the singlecolumn/single row rectangles; for each single column, combiningcontiguous single column/single row rectangles to thereby form at leastone multi row/single column rectangle; combining contiguousmulti-row/single column rectangles that have the same major dimensioncoordinate to form the set of non-overlapping rectangular regions. 9.The method of claim 8, wherein rows are along the minor axis and columnsare along the major dimension.
 10. In a Cartesian space defined by afrequency domain and a time domain, a method of transforming a pluralityof over-lapping rectangular regions, in a plane with two orthogonalaxes, one of the axes parallel to a preferred dimension, in to aplurality of non-overlapping rectangular regions, the improvementcomprising an electronic device performing the steps of: splitting theplurality of overlapping rectangular regions into regions in anon-uniform grid and merging the regions along each of the twoorthogonal axes to form non-overlapping rectangular regions, whereinnone of the non-overlapping rectangular regions share a common edgeorthogonal to the preferred dimension.
 11. The method of claim 10,wherein the orthogonal axes are a time domain and a frequency domain andthe preferred dimension is parallel to the time domain.
 12. The methodof claim 10, wherein the orthogonal axes are a time domain and afrequency domain and the preferred dimension is parallel to thefrequency domain.
 13. The method of claim 10, comprising the step ofsuperimposing a virtual grid onto the Cartesian space, wherein each unitof the virtual grid corresponds to an edge of one or more of theplurality of overlapping rectangular regions.
 14. The method of claim13, comprising the step of joining adjacent virtual grid units in thepreferred dimension that are covered by the plurality of overlappingrectangular regions forming a plurality of virtual strips.
 15. Themethod of claim 14, comprising the step of joining adjacent virtualstrips in another dimension that share the same coverage in thepreferred dimension thereby forming virtual non-overlapping rectangularregions in the grid.
 16. The method of claim 15, comprising the steps ofdetermining corresponding coordinates in the Cartesian space for thevirtual non-overlapping rectangular regions.
 17. In a time-frequencywindow of interest, a method of excising the overlapping portion of twodimensional rectangular areas within a plane defined by orthogonal axesof time and frequency, and a preferred dimension parallel to one of theorthogonal axes, comprising the step of transforming the rectangularareas into non-overlapping rectangular areas, the improvement comprisingan electronic device performing the steps of: splitting the rectangularareas into regions in a non-uniform grid and merging the regions alongthe time and frequency axes to form non-overlapping rectangular areas,wherein none of the non-overlapping rectangular areas share a commonedge orthogonal to a preferred dimension.
 18. A multi-channel detectionsystem for transforming a plurality of overlapping two-dimensionalrectangular regions into non-overlapping two dimensional rectangularregions wherein each non-overlapping region has a maximum extent in amajor dimension parallel to one of two orthogonal axes, comprising:means for splitting the overlapping regions into marked regions in anon-uniform grid; and, means for merging the marked grid regions alongthe major dimension and along the minor dimension to formnon-overlapping regions, wherein no two of the non-overlappingrectangular region have adjacent edges orthogonal to the majordimension.
 19. A system for reconstructing a coverage area defined byoverlapping two dimensional rectangular regions with non-overlapping 2-Drectangular regions comprising: means for forming a non-uniform 2dimensional grid using the coordinates of the overlapping rectangularareas; means for splitting the overlapping 2D rectangular areas intonon-uniform grid units; and means for combining adjacent tagged gridunits into non-overlapping rectangular regions defined by major edgesand minor corners.